Energy and Utilities Leaders Look Beyond AI Adoption to Build Trusted Data Foundations

Cloudera, a data and AI platform company that brings AI to data anywhere, released energy and utilities findings from its latest research report, The Data Readiness Index 2026. The report reveals that data readiness has emerged as a critical factor in AI success for energy and utilities organizations.While many have established the foundations for AI, ongoing challenges related to data accessibility, governance, and infrastructure performance are preventing them from fully operationalizing AI and realizing value at scale. 

As energy and utilities providers modernize infrastructure, manage increasingly distributed energy resources, and pursue grid reliability initiatives, AI is becoming a critical tool for operating the infrastructure that underpins daily life and economic activity. AI-powered technology offers significant potential to improve grid reliability, prevent costly outages, optimize asset performance and uptime, accelerate renewable energy integration, and strengthen infrastructure resilience. Realizing those benefits, however, depends on accessing, governing, and operationalizing data across geographically dispersed environments while maintaining reliability, security, and regulatory compliance. 

The research suggests that many energy and utilities organizations have established a strong foundation for AI readiness. Eighty-six% (86%) of respondents report visibility into where their data resides, while 79% say they can access their organization’s data regardless of format or location. Additionally, 65% report that all or nearly all of their data is governed, reflecting continued investment in data management and modernization initiatives.  

However, challenges remain as organizations work to scale AI initiatives. For 25% of energy and utilities respondents, cost overruns emerged as the leading reason AI and analytics investments fail to deliver expected returns. The findings also highlight workforce readiness challenges, with data literacy and training identified as a significant obstacle to effective data use.  

Despite these challenges, the industry appears well-positioned for continued AI adoption. Compared to other sectors surveyed, energy and utilities organizations reported relatively few operational disruptions caused by infrastructure performance, suggesting many have already established the foundational data environments required to support large-scale analytics and AI workloads.  

“Energy and utilities providers face a unique challenge: delivering safe, reliable, and affordable services while modernizing infrastructure and managing growing demand and grid complexity,” said Morgan Bowling, director, global industry AI solutions, industrial and manufacturing, Cloudera. “AI can play a transformative role, but only if organizations can trust and access the data that powers it. The leaders in this next phase of AI adoption will be those that create a strong data foundation capable of supporting real-time intelligence across the grid, the field, and the enterprise.” 

The findings highlight that data readiness is becoming a prerequisite for the next gen of AI-powered energy operations. As organizations look to apply AI across gen assets, transmission networks, field operations, and customer-facing systems, success will depend on the ability to bring AI to trusted data wherever it resides. Those that establish strong data foundations will be best equipped to scale AI securely, improve operational performance, and adapt to the evolving demands of the energy landscape.